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AIMFP

AIMFP

by aryanduntley
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

add_flow

Add a project flow with name and AI generation flag to manage functional programming tasks and directives.

Instructions

Add project flow

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>",
      "ai_generated": "<ai_generated>"
    },
    "name": "add_flow"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesFlow name
descriptionNoFlow description
ai_generatedYesTrue if AI-generated
confidence_scoreNoConfidence score 0-1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.37.0

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate a mutation (readOnlyHint=false) and non-destructive (destructiveHint=false). The description adds no additional behavioral details, such as whether changes are immediately persisted, if authorization is required, or if the tool creates a default flow with other fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at three words, with no wasted text. However, it may be too terse for a tool with four parameters; a slightly more informative description could be provided without sacrificing brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and moderate complexity (4 parameters, 2 required), the description fails to explain what the tool returns (e.g., the created flow object) or side effects like duplicate handling. Context from sibling tools suggests flows are used in a broader system, but this is not referenced.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so each parameter already has a clear description. The tool description does not add any new semantic context for the parameters, making it adequate but not enhancing understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Add project flow' clearly states the verb 'Add' and the resource 'project flow', indicating creation of a new flow. It distinguishes from sibling tools like 'add_file_to_flow' which add a file to an existing flow. However, it does not elaborate on what a flow represents, which might be understood from context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as 'update_flow' or 'get_all_flows'. There is no mention of prerequisites like unique naming, required project context, or constraints on usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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